Tag Archives: Artificial Intelligence

Our news and activity streams are buzzing with articles, blogs, analyst reports and social media hype around the topic of “AI”. It’s a fairly loosely defined topic that covers an enormous spectrum of disciplines, from big data and predictive analytics, to machine learning, natural language processing, automation and robotics. Depending on who you listen to, it’s either the most important technological breakthrough since the invention of electricity, or it heralds the end of civilisation as we know it! Extreme scenarios are most certainly fantasies and should be discounted. The most likely outcome is neither extremely negative nor extremely positive.

What tends to focus our attention are the stories about how AI and “intelligent” machines are replacing roles, jobs, or even professions. What is the real truth behind these stories?

There is no doubt that workplace automation is becoming more widespread, and today’s AI-enabled, information-rich tools are increasingly able to handle jobs that in the past have been exclusively done by people (including tax returns, language translations, accounting, even some types of surgery) – automation is destined to have profound implications for the future world of work.

McKinsey recently reported that 30 percent of activities for 60 percent of occupations are now technically automatable.

Recent advances in robotics, machine learning, and AI are pushing the frontier of what machines are capable of doing in all facets of business and the economy. Physical robots have been around for a long time in manufacturing, but more capable, more flexible, safer, and less expensive robots are now engaging in ever expanding activities and combining mechanization with cognitive and learning capabilities—and improving over time as they are trained by their human co-workers on the shop floor, or increasingly learn by themselves.

Massive amounts of data that can be used to train machine learning models are being generated, for example through daily creation of billions of images, online click streams, voice and video, mobile locations, and sensors embedded in the Internet of Things. The combination of these breakthroughs has led to spectacular demonstrations like DeepMind’s AlphaGo, which defeated a human champion of the complex board game ‘Go’ in March 2016.

New milestones are being achieved in numerous areas, often with performance beyond human capabilities. In 2016, for example, Google’s DeepMind and the University of Oxford applied deep learning to a huge data set of BBC programs to create a lip-reading system that is more accurate than a professional lip-reader.

There are numerous examples of how machine learning is being used to augment human decision making in healthcare, aircraft maintenance, oil and gas operations, recruitment, insurance claims processing and law. There is barely a sector that is not engaged in some way in exploring the use of AI and automation technologies to improve productivity or accuracy.

One of the more practical roles for AI over the past few years has been to automate administrative tasks and decisions. Companies typically have thousands of such tasks and decisions to perform, and it was realized that if they could be expressed in a formal logic, they could be automated. A key feature of this type of automation is machine/deep learning and robotic process automation (RPA) – which, contrary to its name does not involve actual robots; it makes use of workflow and business rules technology to perform digital tasks. The technology makes it relatively easy to automate structured digital tasks that involve interaction with multiple information systems.

So, what does all of this new technology mean in terms of jobs? Most analysts are agreed that whilst many routine tasks and functions – both physical and cognitive – are being automated, this does not necessarily mean that we are heading for mass unemployment as the machines take over. Perhaps one of the most extensive research programmes into the impact of AI on jobs and skills has been undertaken by Nesta. It has published its findings in the report: The Future of Skills: Employment in 2030. Well worth a read. The report highlights that:

skills that are likely to be in greater demand in the future include interpersonal skills, higher-order cognitive skills, and systems skills.

the future workforce will need broad-based knowledge in addition to the more specialised skills that are needed for specific occupations.

dialogues that consider automation alone are dangerous and misleading since they rarely take account of globalization, an ageing population and the rise of the green economy.

Perhaps the last word on where AI and automation is having (or will have) the most impact should go to Gil Press at Forbes, who identifies the sectors and functions as follows:

Industrial Robots: Physical robots that execute tasks in manufacturing, agriculture, construction, and similar verticals with heavy, industrial-scale workloads. The Internet of Things, improved software and algorithms, data analytics, and advanced electronics have contributed to a wider array of form factors, ability to perform in semi- and unstructured environments, and the “intelligence” to learn and operate autonomously.

Retail and Warehouse Robots: Physical robots with autonomous movement capabilities used in retailing and/or warehousing. Amazon deploys this technology throughout its warehouses.

Virtual Assistants: Personal digital concierges that know users and their data and are discerning enough to interpret their needs and make decisions on their behalf.

He goes on to say: “There is no question that we will continue to see in the future the same disruption in the job market that we have witnessed in the last sixty-plus years of computer technology creating and destroying jobs (like other technologies that preceded it). The type of disruption that has created Facebook and Tesla. Facebook had a handful of employees in 2004 and today employs 20,000. Tesla was founded in 2003 and today has 33,000 employees. Whether AI technologies progress fast or slow and whether AI will continue to excel only at narrow tasks or succeed in performing multi-dimensional activities, entrepreneurs like Zuckerberg and Musk…will seize new business opportunities to both destroy and create jobs. Humans, unlike bots and robots (now and possibly forever), adapt to changing circumstances.”

One thing we can be sure of: the rate of change will continue to accelerate, and if we wish to remain relevant in our chosen professions, we need to identify and refine the skills that can’t easily be automated. Whether that’s a shrinking or expanding environment remains to be seen.

Please note this post contains the personal views of the author and are not connected with her employer

I recently had the pleasure of attending the 14th Perfect Information Conference (PIC2017) in Bath, England. This annual event, hosted by the company Perfect Information (part of Mergermarket), brings together leaders and senior members of information services from within financial and professional service organisations with representatives of their content and service vendor partners. The high number of repeat attendees confirms the conference’s value. This year’s programme theme was ‘Man vs Machine: comrade or threat’. For me (spoiler alert!) the whole event reaffirmed the current and future value and potential of humans in an increasingly technological world.

The conference programme includes keynote speakers, more practical workshops and hot topic think tanks (and of course some socialising!). What seemed to me initially a rather disparate set of topics actually transitioned from the big picture of artificial intelligence (AI) and its future to more practical implications of change for businesses today. Having worked myself for a short time at the (original) Turing Institute in the early days of AI, it was fascinating to hear where AI is today.

AI is all around us, was the clear answer from the three speakers who focused on this topic, respectively Marc Vollenweider (Evalueserve), Anton Fishman (Fishman & Partners) and Nicolas Bombourg (Report Linker). Marc, who is transitioning from CEO to Chief Strategist of Evalueserve, spoke about the explosion of data sets, and the business value to be derived from cheap but effective analytic use cases. Anton alluded to the ‘perfect storm’ of converging technologies that is affecting the world of machine learning. Nicolas described Artificial Narrow Intelligence (ANI) – where we are now (machines specialising in one are) – and how we are moving closer to Artificial General Intelligence (AGI) – machines thinking like humans – and even beyond to Artificial Super Intelligence (ASI).

Are we heading for dystopia or utopia? There were references to sobering statistics about the predicted negative impact on job numbers, for example, Mark Carney’s speech on the ‘hollowing out of the middle classes’ and Frey & Osborne’s research in to the future of work in the US. Ultimately however the message was upbeat. Marc is definite that ‘insights need humans’, and has written about the benefits of combining mind+machine. Anton referred to the opportunity for the ‘rise of humans’ that Microsoft’s Envisioning Officer has described. The message is that technology is supporting humans, expanding our potential – AI is already invisibly enhancing our world. This is not a zero sum game for mankind, even if it does create much management uncertainty, ethical dilemmas, job redefinition and the need for a new ‘social contract’.

What were my key takeaways from these speakers and all the other interaction at the conference for me in my role as an information professional and services manager?

Information professionals do have roles to play in the new data economy, where the flow of data is driving innovation and growth, as long as they are open minded and upskill. Marc has elsewhere talked about the emerging role of the information engineer in creating analytics solutions. McKinsey recently re-recognised the need for translators between technology and information, reaffirming the need to link IT, understanding of data, and business need. Establishing the veracity of data is of course a traditional information professional skill.

Information professionals need to engage with the business, via new channels such as their workplace’s Chief Information or Data Officer (CIO, CDO) – wherever analytics are happening – and change the scope of their services to help the business build effective productivity tools and new trigger-based workflows, and avoid data lakes that become data graveyards.

Change management is important – keeping people engaged, attracting new talent, enabling career progression, as well as ensuring effective use of the new tools and data by the business.

And for those directly engaged in buying and selling data there are reminders of the early days of the internet and outsourcing in the challenges of delivering and consuming data in new ways – for the vendors, what to build first for which client, how to protect the data, how to charge for it; for their clients where to focus efforts, who will eat the costs; and for both parties, how to deal with the increased visibility of data quality issues.

Overall the Conference ended on an optimistic note in contrast to the anxieties of the 2016 Conference (as described by in the opening session of the conference by Robin Neidorf) and inspite of the seismic political changes we have seen in the UK and USA in the last twelve months. It will be interesting to hear how things have further changed for the attendees by the same time next year.